Smartphones have become indispensable in our daily lives and can do almost everything, from communication to online shopping. However, with the increased usage, cybercrime aimed at mobile devices is rocketing. Smishing attacks, in particular, have observed a significant upsurge in recent years. This problem is further exacerbated by the perpetrator creating new deceptive websites daily, with an average life cycle of under 15 hours. This renders the standard practice of keeping a database of malicious URLs ineffective. To this end, we propose a novel on-device pipeline: COPS that intelligently identifies features of fraudulent messages and URLs to alert the user in real-time. COPS is a lightweight pipeline with a detection module based on the Disentangled Variational Autoencoder of size 3.46MB for smishing and URL phishing detection, and we benchmark it on open datasets. We achieve an accuracy of 98.15% and 99.5%, respectively, for both tasks, with a false negative and false positive rate of a mere 0.037 and 0.015, outperforming previous works with the added advantage of ensuring real-time alerts on resource-constrained devices.

翻译：智能手机已成为日常生活中不可或缺的工具，从通信到在线购物几乎无所不能。然而，随着使用频率的增加，针对移动设备的网络犯罪急剧上升。近年来，短信钓鱼攻击尤其呈现出显著增长趋势。攻击者每天创建新的欺诈性网站，平均生命周期不足15小时，这一问题进一步加剧了传统恶意URL数据库维护策略的失效。为此，我们提出了一种新颖的设备端流水线COPS，该流水线能智能识别欺诈性消息和URL的特征，实时向用户发出警报。COPS是一个轻量级流水线，其检测模块基于大小为3.46MB的解耦变分自编码器，用于短信钓鱼和URL钓鱼检测，并在开放数据集上进行基准测试。在两个任务中，我们分别实现了98.15%和99.5%的准确率，假阴性率和假阳性率分别仅为0.037和0.015，优于以往工作，且额外具有在资源受限设备上确保实时警报的优势。